Swing leg placement is vital to stability in legged robots and animals. Without placing the feet into proper target points on the ground, legged systems fail to balance dynamically. These targets have been identified with simplified point-mass models including the linear inverted pendulum for standing and walking, and the spring-mass system for running. The models predict foot placement targets which stabilize gait in response to a disturbance such as an external push or an unexpected change in the ground level. However, they do not reveal how the segmented legs of humans and humanoids can actually reach these targets.
The most common approach to generating swing leg motions in humanoids uses trajectory planning and tracking. In this approach, trajectories for all leg joints are planned either based on optimization over deviations from the foot placement targets or by spline interpolation between consecutive placement targets. Once generated, these reference trajectories are tracked via proportional-derivative control at the joint levels. Planning and tracking of swing-leg trajectories requires central control over all leg joints, which limits the application of this approach to powered prosthetic limbs which replace only part of the human body.
Although alternative approaches have been explored in rehabilitation robotics, tracking predefined joint patterns remains the state of the art in the control of powered artificial legs. For instance, current leg prostheses mimic human joint impedances that have been recorded in experiments. Bound to these predefined patterns, handling gait disturbances still requires event detection, automatic classification, and the implementation of deliberate joint trajectories to counter these disturbances, hampering practical implementations of autonomous powered legs that achieve robust swing placement under large disturbances.
Animal and human legs by contrast demonstrate robust swing placement with remarkable autonomy. From early work on mesencephalic cats to recent investigations on paralyzed cats and rats with drug administration and epidural stimulation, experiments have shown that animals can seamlessly adapt their leg behavior throughout stance and swing, to different speeds and gaits without central planning by the brain. These observations suggest that a substantial part of leg control in animal and human locomotion is generated by spinal circuits which adapt to changes in the environment.